On the generalized domain of attraction of the multivariate normal law and asymptotic normality of the multivariate Student t-statistic

Yuliya V. Martsynyuk

Journal of Multivariate Analysis, 2013, vol. 114, issue C, 402-411

Abstract: It is well-known that if a random vector X is in the generalized domain of attraction of the multivariate normal law (GDAN), then all its components are in the domain of attraction of the normal law (DAN) and, moreover, the Euclidean inner products of X with all the nonrandom vectors of unit Euclidean norm are also in DAN. However, these two implications are known to be nonreversible in general. In this paper, a condition is given under which these implications are proved to become reversible, and thus characterizations of GDAN. Large enough classes and an example of random vectors satisfying this condition are provided. Also, the multivariate Student t-statistic that is based on independent copies of a random vector X satisfying this condition is proved to be asymptotically standard normal only if X is in GDAN. A corollary to the thus established result parallels a previous resolution of this problem for a spherically symmetric X in the literature.

Keywords: Generalized domain of attraction of the d-variate normal law; Full random vector; Domain of attraction of the normal law; Slowly varying function at infinity; Sample correlation matrix; Cramér–Wold device; Spherically symmetric random vector; Pareto distribution; (Left) Cholesky square root of a matrix; Symmetric positive definite square root of a matrix; d-variate Student t-statistic (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1016/j.jmva.2012.08.012

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